Little’s Law: find the work waiting in your business

Use Little’s Law to understand waiting work, compare queue size with output and find practical improvements without losing delivery reliability or quality.

How does Little’s Law reveal work waiting in your business?

Little’s Law links average open jobs, completion rate and time in the system. Use figures from the same process to find where work waits and test whether smaller queues improve flow. Check quality and delivery reliability alongside queue size before changing staffing, stock levels or the promises you make to customers.

Keep these in mind

  • Measure jobs inside one clearly defined process.
  • Average lead time includes waiting as well as hands-on work.
  • Less unfinished work helps only if completed output and service quality hold up.
Approved job → Waiting reason → Next step → Ready for collection
Track one boundary so open jobs and completed jobs describe the same flow.

Choose a boundary before doing the arithmetic

A repair shop might measure from a customer approving a repair to the repaired item being ready for collection. It should not count enquiries as open repairs while measuring completions only for approved jobs. Those are different populations.

The relationship is usually written L = λW. L is average work in progress, λ is the average flow rate and W is average elapsed time. The Illinois Business Innovation Services teaching material presents the same relationship for production flow.

Use consistent units and a representative period.

For a growing backlog, a short measurement window or a seasonal rush, the simple calculation needs care. It is an average relationship, not a promised completion date for every customer.

A repair queue in numbers

Consider an illustrative shop with an average of 24 approved repairs open and eight repairs completed per working week. Average elapsed time within that boundary is 24 ÷ 8 = three working weeks. A repair requiring two hours at the bench can still spend weeks waiting.

Suppose the shop reduces average open repairs to 16 while sustaining eight completions a week. The corresponding average becomes two weeks. Compare accepted work, margin and service quality before extending the change.

Customers may have left, job complexity may have changed or technicians may be working overtime.

Illustrative averages using one approved-repair boundary
MeasureBeforeAfter a proposed change
Open repairs2416
Completed repairs per week88
Implied average elapsed time3 weeks2 weeks

Try it with your queue

Use averages from the same process and time period.

3 weeks average time in the system

Average open jobs ÷ completions per week. This is a planning average, not a promised delivery time.

Calculated in your browser. Numbers are not saved or sent.

Find what the queue is waiting for

Take the ten oldest jobs and ask one concrete question about each: what prevents the next step today? Useful reasons include awaiting a part, awaiting customer approval, awaiting a technician and awaiting a quality check. Give the reason an owner and a next review date.

The Lean Enterprise Institute’s standardized-work guidance includes process-capacity analysis. Here, the practical task is to separate a genuine shortage of skilled bench hours from missing instructions or parts. Adding a technician will not resolve an unapproved quotation.

Connect the queue to cash with care. Parts bought for unfinished jobs and unissued invoices can tie up money. Lead time alone does not calculate that amount.

Record deposits, purchased materials and billing milestones separately.

Run a two-week queue experiment

Begin with one service category whose jobs are reasonably comparable. Count open work at the same time each day and record completions daily. Keep cancelled jobs visible so they do not disappear from the story.

  1. Write the process start and finish in one sentence.
  2. Count daily open jobs and average them over the observation period.
  3. Divide completed jobs by the number of working days in the same period.
  4. Compare calculated elapsed time with actual start-to-finish dates for completed jobs.
  5. Remove one recurring waiting reason and repeat the measurement.

Keep the improvement useful

Review customer complaints, rework and missed promises beside queue size. A smaller queue with more rejected work or rushed quality is not automatically a better business. Separate urgent repairs from standard repairs if they follow very different paths.

Keep the blockage, responsible person and next check beside each job. Confirm progress with the person doing the work, especially when a status changed during a call. Compare the queue at the same time each week so an apparent improvement is not simply a different counting method.

Save the reason for an exception while everyone still remembers it.

Common questions

Which figures belong in a Little’s Law calculation?

Use average open work, average completions and elapsed time from the same process and period. Keep units consistent and investigate changes in demand before treating the result as representative.

How can we check whether a smaller queue helped?

Compare delivery reliability, quality, rework and good output as well as queue size. Follow a similar mix of jobs so moving difficult work elsewhere does not look like an improvement.

Sources & further reading

Primary references for the facts and frameworks discussed. Worked examples and recommendations are Daltn’s own analysis.

  1. Introduction to Lean, Illinois Business Innovation Services ↗

    Supports the WIP, throughput and lead-time relationship on slides 15–16.

  2. Standardized Work, Lean Enterprise Institute ↗

    Explains capacity sheets and process observation.

Published by the team building Daltn. Comparisons are first-party analysis, not independent reviews. Our editorial approach.

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